The analysis of abundance and of the dynamic rates governing their change lies at the core of ecology and its applications such as conservation and wildlife management. Metapopulation designs, where repeated measurements of some quantity such as counts or distance measurements are made at a collection of sites, underlie a vast number of studies in ecology and management. Inference about such data is conveniently based on hierarchical models, where one submodel describes the underlying true state of the process (e.g., abundance at a site) and another submodel describes the observation process that connects the true state to the observations.

In recent years, much progress has been made in the development of methods and computer algorithms to fit hierarchical models. In particular, Bayesian statistical analysis and the general-purpose Bayesian software package WinBUGS have opened up entirely new possibilities for ecologists to conduct complex population analyses. On the other hand, the R package unmarked contains a wealth of functions to analyse hierarchical models of abundance in a frequentist mode of inference.

This course introduces key hierarchical models used in the analysis of abundance and its spatial and temporal patterns, and provides both Bayesian and the frequentist methods for their analysis. We use package unmarked in R as well as WinBUGS and JAGS to fit and understand some of the most widely used models for the analysis of animal and plant populations. These include:- binomial (Royle 2004) and multinomial N-mixture models (e.g., removal, double-observer) for the analysis of distribution and abundance,- CAR modeling of spatial autocorrelation in abundance- hierarchical distance sampling models (e.g., Royle et al. 2004, Conn et al. 2012),- dynamic models of abundance (Royle & Dorazio 2008; Dail & Madsen 2011)

This is an intermediate-level workshop with about 80% spent lecturing and 20% on solving exercises. A working knowledge of modern regression methods (GLMs, mixed models) and preferentially of program R or another programming language is required. No previous experience with program WinBUGS is assumed (but, of course, it is beneficial).

Please bring your own laptops and install a recent version of R, with the latest version of package unmarked, plus JAGS and/or WinBUGS 1.4., with the upgrade patch and the immortality key decoded (in this order, only for the latter). OpenBUGS should work for most of what we do.